典型文献
The control of moldy risk during rice storage based on multi-variate linear regression analysis and random forest algorithm
文献摘要：
Clarifying the mechanism of fungi growth is of great significance for maintaining the quality during grain stor-age.Among the factors that affect the growth of fungi spores,the most important factors are temperature,moisture content and storage time.Therefore,through this study,a multivariate linear regression model among several important factors,such as the spore number and ambient temperature,rice moisture content and storage days,were developed based on the experimental data.In order to build a more accurate model,we introduce a random forest algorithm into the fungal spore prediction during grain storage.The established regression models can be used to predict the spore number under different ambient temperature,rice moisture content and storage days during the storage process.For the random forest model,it could control the predicted value to be of the same order of magnitude as the actual value for 99％of the original data,which have a high accuracy to predict the spore number during the storage process.Furthermore,we plot the prediction surface graph to help practitioners to control the storage environment within the conditions in the low risk region.
文献关键词：
中图分类号：
作者姓名：
Yurui Deng;Xudong Cheng;Fang Tang;Yong Zhou
作者机构：
State Key Laboratory of Fire Science,University of Science and Technology of China,Hefei 230027,China;Academy of National Food and Strategic Reserves Administration,Beijing 100037,China
文献出处：
引用格式：
[1]Yurui Deng;Xudong Cheng;Fang Tang;Yong Zhou-.The control of moldy risk during rice storage based on multi-variate linear regression analysis and random forest algorithm)[J].中国科学技术大学学报,2022(01):43-51
A类：
B类：
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AB值：
0.472709
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